This invention generally relates to imaging for the purpose of medical diagnosis. In particular, the invention relates to methods for imaging tissue and blood flow by detecting ultrasonic echoes reflected from a scanned region of interest in a human body.
Conventional ultrasound scanners are capable of operating in different imaging modes. In the B mode, two-dimensional images can be generated in which the brightness of each display pixel is derived from the value or amplitude of a respective acoustic data sample representing the echo signal returned from a respective focal position within a scan region.
In B-mode imaging, an ultrasound transducer array is activated to transmit beams focused at respective focal positions in a scan plane. After each transmit firing, the echo signals detected by the transducer array elements are fed to respective receive channels of a receiver beam-former, which converts the analog signals to digital signals, imparts the proper receive focus time delays and sums the time-delayed digital signals. For each transmit firing, the resulting vector of raw acoustic data samples represents the total ultrasonic energy reflected from a succession of ranges along a receive beam direction. Alternatively, in multi-line acquisition two or more receive beams can be acquired following each transmit firing.
In conventional B-mode imaging, each vector of raw acoustic data samples is envelope detected and the resulting acoustic data is compressed (e.g., using a logarithmic compression curve). The compressed acoustic data is output to a scan converter, which transforms the acoustic data format into a video data format suitable for display on a monitor having a conventional array of rows and columns of pixels. This video data is referred herein as xe2x80x9craw pixel intensity valuesxe2x80x9d. The frames of raw pixel intensity data are mapped to a gray scale for video display. Each gray-scale image frame, hereinafter referred to as xe2x80x9cgray-scale pixel intensity valuesxe2x80x9d, is then sent to the video monitor for display. In the case where a one-to-one gray-scale mapping is in effect, the raw and gray-scale pixel intensity values will be one and the same.
In ultrasound imaging, the diagnostic quality of images presented for interpretation may be diminished for a number of reasons, including incorrect settings for brightness and contrast. If one tries to improve the image with available methods for adjusting brightness and contrast, this has the undesirable result of increasing the pixel intensity values corresponding to the near-field region as well. Because the near-field region is inherently bright, the desired result is generally not achieved. There is a need for a filtering technique that will enhance the image brightness and contrast without affecting the image in the near-field region.
The invention is directed to improving images, e.g., ultrasound images, by means of contrast enhancement. The invention claimed herein is not limited in its application to ultrasound imaging systems.
One embodiment of the present invention is a method for adjusting contrast in an ultrasound image. In another embodiment, both contrast and brightness are adjusted. The contrast and brightness are adjusted by processing global pixel intensity data to form a set of data representing a histogram. An algorithm is then employed to filter the pixel intensity values as a function of certain characteristics of the histogram data. The algorithm is designed to enhance contrast and brightness without affecting the near-field region in the ultrasound image. The processes that implement the algorithm will be generally referred to herein as xe2x80x9cfilteringxe2x80x9d. The filtering operations may be performed by a dedicated processor or by a fast general-purpose computer.
Another embodiment of the invention comprises a system for enhancing contrast and, optionally, brightness in an ultrasound image. The system incorporates a computer programmed to filter pixel intensity values in accordance with the aforementioned algorithm.
The first step of the algorithm is to compute a set of histogram data from a set of pixel intensity values generated by an image processor. The histogram data comprises counts representing the number of pixels having pixel intensity values belonging to a respective bin, each bin being defined to encompass non-overlapping subsets of pixel intensity values, each subset comprising either a different pixel intensity value or a different range of pixel intensity values. In the next step, the pixel intensity values are decreased in those bins having pixel intensity values in a first range of lowest pixel intensity values. This decrease in pixel intensity values is implemented by multiplying each pixel intensity value in the first range by a multiplication factor less than unity and greater than zero. This increases the contrast of the image. In a third step, the pixel intensity values are decreased in those bins having pixel intensity values in a second range of pixel intensity values excluding at least a third range of highest pixel intensity values, wherein the first through third range do not overlap with each other. This decrease in pixel intensity values in the second range is implemented by logarithmic filtering each pixel intensity value in the second range. This further increases the contrast of the image.
Additional steps of the algorithm are directed to enhancing the brightness of the image by either increasing or decreasing each pixel intensity value. Optionally the image quality can be further improved by stretching the histogram using the ATO function.
The method disclosed herein uses the image""s global information to optimize image brightness and contrast. It changes the grayscale values to the optimal region of the histogram. The method improves the system operator""s productivity and throughput while improving image quality.